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The majority of esophageal squamous dysplasia (ESD) patients progress slowly, while a subset of patients can undergo recurrence rapidly or progress to invasive cancer even after proper treatment. However, the molecular mechanisms underlying these clinical observations are still largely unknown.

The long-standing Gaussian product inequality (GPI) conjecture states that E[∏j=1n∣Xj∣yj]≥∏j=1nE[∣Xj∣yj]E\left[{\prod }_{j=1}^{n}{| {X}_{j}| }^{{y}_{j}}]\ge {\prod }_{j=1}^{n}E\left[{| {X}_{j}| }^{{y}_{j}}] for any centered Gaussian random vector (X1,…,Xn)\left({X}_{1},\ldots ,{X}_{n}) and any non-negative real numbers yj{y}_{j}, j=1,…,nj=1,\ldots ,n. In this study, we describe a computational algorithm involving sums-of-squares representations of multivariate polynomials that can be used to resolve the GPI conjecture. To exhibit the power of the novel method, we apply it to prove new four- and five-dimensional GPIs: E[X12mX22X32X42]≥E[X12m]E[X22]E[X32]E[X42]E\left[{X}_{1}^{2m}{X}_{2}^{2}{X}_{3}^{2}{X}_{4}^{2}]\ge E\left[{X}_{1}^{2m}]E\left[{X}_{2}^{2}]E\left[{X}_{3}^{2}]E\left[{X}_{4}^{2}] for any m∈Nm\in {\mathbb{N}}, and E[∣X1∣yX22X32X42X52]≥E[∣X1∣y]E[X22]E[X32]E[X42]E[X52]E\left[{| {X}_{1}| }^{y}{X}_{2}^{2}{X}_{3}^{2}{X}_{4}^{2}{X}_{5}^{2}]\ge E\left[{| {X}_{1}| }^{y}]E\left[{X}_{2}^{2}]E\left[{X}_{3}^{2}]E\left[{X}_{4}^{2}]E\left[{X}_{5}^{2}] for any y≥110y\ge \frac{1}{10}.

ObjectiveTo identify the optimal parameters of gross movement interventions to yield the strongest effects on physical fitness among children aged 3–10 years and to provide a reference for the development of gross movement interventions to improve the physical fitness of children.BackgroundThere has been a global decline in children’s physical fitness. Previous studies have shown that gross movement interventions can improve children’s physical fitness, but the optimal intervention parameters for achieving the strongest effects have yet to be determined. Therefore, we conducted this meta-analysis to determine the optimal intervention parameters for yielding the strongest effects on children’s physical fitness.MethodsWe searched the Web of Science, PubMed, China Biology Medicine, China National Knowledge Infrastructure, Wanfang Data, and China Science and Technology Journal databases to identify randomized controlled trials on the effects of gross movement interventions (walking, running, jumping, throwing, batting, rolling, spinning, catching, and leg lifting) on children’s physical fitness (upper-body strength, lower-body strength, explosive power, speed, flexibility, and balance). We included studies published up to September 2023. The inclusion and exclusion criteria were developed based on the PICOS framework, and the quality of the included studies was evaluated. Subgroup analysis was performed using Review Manager 5.3, and the data were pooled using a random effects model to obtain the SMD (or WMD) and 95% confidence intervals (CIs).ResultsA total of 23 studies involving 2007 healthy children aged 3–10 years met the inclusion criteria. Gross movement interventions significantly improved the explosive power of children aged 3–10 years [WMD, 6.2]. The most effective intervention duration was 16–18 weeks [WMD, 0.45]. The most effective intervention frequency was one session per week [WMD, 1.06]. The optimal duration of single sessions was 60 min [WMD, 0.47]. Children aged 7–10 years [WMD, 1.41] showed the most significant improvements in physical fitness after gross movement interventions.ConclusionGross movement interventions had a positive effect on the physical fitness of children aged 3–10 years. The optimal intervention parameters include 60-min sessions once a week across a total duration of 16–18 weeks.

Diolefin elastomers play an important role in production and life, but their unsaturated structure leads to extreme vulnerability to heat and oxygen attack, so research into the aging of diolefin elastomers has been a hot spot in the industry. To overcome this limitation, a strategy based on the thermal decomposition of 1,1′-Azobis(cyclohexanezonitrile) (Azo) is devised, which forms stabilized compounds with imine groups during the heat process and captures radical. The diolefin elastomer was combined with azo, and isoprene rubber (IR) is chosen as a model material. Azo was added to IR to prepare the composite material (IR-Azo), and the thermo-oxidative resistance of the composite was significantly improved. Such as, after being exposed to thermo-oxidative conditions for 24 h, IR-Azo showed a tensile strength of 14.96 MPa with a retention rate of 68.25% which exceeded that of many traditional antioxidants. This study provides new insights into the development of elastomers with excellent thermo-oxidative resistance.

C25H22O3, orthorhombic, P212121 (no. 19), a = 6.1768(2) Å, b = 11.2198(5) Å, c = 27.5938(11) Å, V = 1912.32(13) Å3, Z = 4, R gt(F) = 0.0319, wR ref(F 2) = 0.0872, T = 100(2) K.

Nosocomial infection control personnel are crucial in ensuring the nosocomial infection management and the implementation of prevention and control measures. The level of their job competency directly determines the quality and standard of nosocomial infection management. This article reviews the research progress of competency requirements and evaluation indicators of nosocomial infection personnel domestically and internationally. It also summarizes the current gaps and primary reasons behind these gaps in China’s research， so as to offer insights for the future development and improvement of the comprehensive capabilities of these professionals.

Abstract In order to quantitatively calculate the critical depth and critical load of mines affected by rock burst, and to achieve effective prevention and control of rock burst in coal mines, this paper proposes a mechanical model for predicting the occurrence of rock burst in coal mine roadways based on catastrophe theory. Additionally, a theoretical calculation formula for initiating rock burst is derived. The first step was to establish a mechanical analysis model, which directly correlated with the in-situ stress, physical and mechanical characteristics of the coal-rock mass, and engineering structural parameters. Following this, a mechanical instability criterion was derived for the key load-bearing circle within the surrounding rock of the roadway. In the final step, the critical depth and load for rock burst initiation were verified for 25 distinct coal mines in China that were prone to rock burst hazards. The research results demonstrate that the discrepancy between the theoretically calculated critical depth and the actual measured statistical values was less than 35%. In addition, the difference between the theoretically determined critical depth and the value calculated by Pan Yishan was less than 32%. Notably, the ratio of the theoretically calculated critical load to the uniaxial compressive strength of the coal-rock mass ranged from 0.38 to 1.93. This aligns with empirical data on rock burst occurrences, as set out in the engineering classification standards for rock masses. These research outcomes substantiated the practical utility of the proposed theory, thereby laying a robust theoretical groundwork for the quantitative control of rock burst.

Abstract Denitrifying bacteria harboring the nitrate reductase S (nirS) gene convert active nitrogen into molecular nitrogen, and alleviate eutrophication in aquaculture water. Suspended particulate matter (SPM) is an important component of aquaculture water and a carrier for denitrification. SPM with different particle sizes were collected from a coastal high-altitude aquaculture pond in Maoming City, China. Diversity, community structure, abundance of nirS-type denitrifying bacteria on SPM and environmental influencing factors were studied using high-throughput sequencing, fluorescence quantitative PCR, and statistical analysis. Pseudomonas, Halomonas, and Wenzhouxiangella were the dominant genera of nirS-type denitrifying bacteria on SPM from the ponds. Network analysis revealed Pseudomonas and Halomonas as the key genera involved in the interaction of nirS-type denitrifying bacteria on SPM in the ponds. qPCR indicated a trend toward greater nirS gene abundance in progressively larger SPM. Dissolved oxygen, pH, temperature, and SPM particle size were the main environmental factors influencing changes in the nirS-type denitrifying bacterial community on SPM in coastal high-altitude aquaculture pond water. These findings increase our understanding of the microbiology of nitrogen cycle processes in aquaculture ecosystem, and will help optimize aquatic tailwater treatment strategies.

IntroductionDurian is one of the tropical fruits that requires soil nutrients in its cultivation. It is important to understand the relationship between the content of critical nutrients, such as nitrogen (N), phosphorus (P), and potassium (K) in the soil and durian yield. How to optimize the fertilization plan is also important to the durian planting.MethodsThus, this study proposes an Improved Radial Basis Neural Network Algorithm (IM-RBNNA) in the durian precision fertilization. It uses the gray wolf algorithm to optimize the weights and thresholds of the RBNNA algorithm, which can improve the prediction accuracy of the RBNNA algorithm for the soil nutrient content and its relationship with the durian yield. It also collects the soil nutrients and historical yield data to build the IM-RBNNA model and compare with other similar algorithms.ResultsThe results show that the IM-RBNNA algorithm is better than the other three algorithms in the average relative error, average absolute error, and coefficient of determination between the predicted and true values of soil N, K, and P fertilizer contents. It also predicts the relationship between soil nutrients and yield, which is closer to the true value.DiscussionIt shows that the IM-RBNNA algorithm can accurately predict the durian soil nutrient content and yield, which is benefited for farmers to make agronomic plans and management strategies. It uses soil nutrient resources efficiently, which reduces the environmental negative impacts. It also ensures that the durian tree can obtain the appropriate amount of nutrients, maximize its growth potential, reduce production costs, and increase yields.

The mineral flotation adsorption equilibrium model is a mathematical model to accurately describe ions/reagents adsorption equilibrium involved in mineral flotation. It is the first time to realize quantitative affinity analysis between mineral surface sites and flotation reagents. There is a lack of scientific explanation for the traditional flotation theory on the surface-active sites, and the adsorption capacity and equilibrium state of flotation reagents are also difficult to clarify, making new reagent design mainly based on empirical methods such as trial-and-error method and compound method. Besides, if selective adsorption, as the core mechanism of flotation, cannot be precisely predicted, the development of intelligent control on flotation process will be seriously limited. This study discussed in detail the construction principle of the mineral flotation adsorption equilibrium model, taking two flotation systems of hematite-quartz and diaspore-kaolinite as examples. The constants containing site density Ns, protonation / deprotonation equilibrium constants Kt1/Kt2, and reagent adsorption constant Kf can be deduced and verified successfully. Based on these constants, mineral surface electricity and ions/reagents adsorption behavior can be forecasted. Furthermore, a kind of kernel algorithm about the mineral flotation prediction system was created through Zeta potential tests and some other verification methods. Using this algorithm, the preliminary and accurate prediction of reagent adsorption on each mineral surface at different conditions can reflect its floatability trend to a certain extent, which helps to shorten the flotation technology development cycle. It is also of great significance in the study of mineral surface reagent adsorption mechanisms, flotation reagent molecular design, and flotation process optimization and intelligent control.

Objective To explore the correlation between the prolongating PR interval of electrocardiogram and the general information and biochemical indicators of diabetes patients with microvascular complications, and the predictive value of diabetes microvascular complications. Methods A total of 217 patients with diabetes who hospitalized in Department of Endocrinology, Xi'an Third Hospital from August 2020 to November 2022 were selected retrospectively. Among them, 149 patients only with diabetes were divided into control group, while 68 diabetes patients with microvascular complications were divided into observation group. The general data and biochemical indexes of all diabetes patients were collected, and the PR interval was measured by standard 12 lead synchronous electrocardiograph. The correlation between PR interval and general data and biochemical indicators in patients with microvascular complications of diabetes were analyzed. The predictive value of PR interval on microvascular complications in diabetes was analyzed by receiver operating characteristic (ROC) curve. Results Age, duration of diabetes, body mass index (BMI), hemoglobin A1c (HbA1c), PR interval in the observation group were higher than those in the control group (P＜0.01). PR interval of diabetes patients with microvascular complications was positively correlated with age, diabetes duration, BMI, HbA1c (P＜0.01). The AUC of PR interval for predicting microvascular complications in diabetes was 0.812 (95%CI:0.752-0.872), the sensitivity was 70.6%, the specificity was 78.5%, and the cut-off value was 212.61 ms. Prolonged PR interval was an independent risk factor for microvascular complications in diabetes (OR=2.475, 95%CI: 1.472-5.120, P＜0.01). Conclusion In patients with microvascular complications of diabetes, the PR interval in electrocardiogrom is significantly prolonged. Prolonged PR interval is an independent risk factor for microvascular complications in diabetes, which is helpful to predict the occurance of diatetic microvascular complications.

BackgroundSevere traumatic brain injuries (TBIs) are an important health issue worldwide, which are associated with harmful side effects. This meta-analysis investigates the cognitive and functional outcomes in severe brain trauma cases. It assesses the impact on memory, verbal and visual abilities, attention, learning, and the presence of depression. The study provides a comprehensive overview of the consequences of severe brain trauma injury on cognitive and functional domains.ObjectiveThe main objective of the current comprehensive meta-analysis study is to assess and analyze the impact of severe TBI on functional and cognitive outcomes, including verbal, visual, attention, learning, memory, and emotional stability.MethodsWe collected data from three online databases, including PubMed, Cochrane Library, and Embase. Case–control trials related to severe TBI association with cognitive and functional outcomes were included. Verbal strength, visual functions, learning abilities, attention, memory, and depression were considered primary outcomes.ResultsWe have included 13 case–control studies with 1,442 subjects in this meta-analysis, which provide adequate data to determine the pooled effect size for targeted outcomes. The effect of severe TBI on the inducement of depression and impairment of memory, verbal, visual, attention, and learning abilities compared to the control group showed statistically significant outcomes (p

A ratiometric fluorescence sensor platform with easy-to-use and accurate is nanoengineered for NH3 quantitative detection and visual real-time monitoring of chicken freshness using smartphones. The ratiometric fluorescent probe formed by combining the zinc ion complex and carbon dots has a double-emitted fluorescence peak. The fluorescence intensity of the complex changed can be clearly observed with the increase of the concentration of ammonia solution under 365 nm wavelength excitation. In order to detect NH3 concentration in gaseous phase, a portable paper-based sensor was designed. The sensor had a good linear relationship with NH3 concentration ranging from 10.0 to 90.0 μmol/L and the LOD value was 288 nM. This fluorescent paper-based sensor was used to check the freshness of chicken breast refrigerated at 4 °C, revealed observable shifts from blue to green. The fluorescent paper-based sensor can detect NH3 concentration in real time and simplify the monitoring process of meat freshness while ensuring accuracy and stability.

Aiming at the main problems existing in the jumping robot, combined with the galago senegalensis monkey's characteristics of small sizes, stable and explosive jumping, a kind of galago senegalensis monkey single leg jumping robot is proposed in this study, and its main structure and control system are designed. Based on the principle of the Stephenson's six-bar linkage, a planar eight-bar linkage for the leg of simulating galago senegalensis monkey robot is designed, and its trajectory is optimized to obtain the bar length parameters with the best jumping ability. The three directions of the robot's jumping are controlled and adjusted, and the double closed-loop feedback control system is used to ensure the stability of the robot's attitude when taking off, soaring in the air, and landing on the ground. Finally, the physical verification model of the robot is established. The total weight is only 395.5 g, and the overall height is 250 mm. The experimental results show that the simulating single leg robot can achieve continuous and stable jumping, the highest jumping speed can reach 20 m/s, and the response time at a jumping height of 100 mm is 0.1 s.

To investigate the effect of adipose-derived stem cells (ASCs) transplantation on radiation-induced lung injury (RILI), Sprague-Dawley rats were divided into phosphate-buffered saline (PBS) group, ASCs group, Radiation + PBS group, and Radiation + ASCs group. Radiation + PBS and Radiation + ASCs groups received single dose of 30 Gy X-ray radiation to the right chest. The Radiation + PBS group received 1 mL PBS suspension and Radiation + ASCs group received 1 mL PBS suspension containing 1 × 107 CM-Dil-labeled ASCs. The right lung tissue was collected on Days 30, 90, and 180 after radiation. Hematoxylin–eosin and Masson staining were performed to observe the pathological changes and collagen fiber content in the lung tissue. Immunohistochemistry (IHC) and western blot (WB) were used to detect levels of fibrotic markers collagen I (Collal), fibronectin (FN), as well as transforming growth factor-β1 (TGF-β1), p-Smad 3, and Smad 3. Compared with the non-radiation groups, the radiation groups showed lymphocyte infiltration on Day 30 after irradiation and thickened incomplete alveolar walls, collagen deposition, and fibroplasia on Days 90 and 180. ASCs relieved these changes on Day 180 (Masson staining, P = 0.0022). Compared with Radiation + PBS group, on Day 180 after irradiation, the Radiation + ASCs group showed that ASCs could significantly decrease the expressions of fibrosis markers Collal (IHC: P = 0.0022; WB: P = 0.0087) and FN (IHC: P = 0.0152; WB: P = 0.026) and inhibit the expressions of TGF-β1 (IHC: P = 0.026; WB: P = 0.0152) and p-Smad 3 (IHC: P = 0.0043; WB: P = 0.0087) in radiation-induced injured lung tissue. These indicated that ASCs could relieve RILI by inhibiting TGF-β1/Smad 3 signaling pathway.

Large pipelines with long term transport of oil and gas resources need to be tested in petrochemical industry nowadays. In this case, a robot which adopts a six-wheel rocker-bogie mobile mechanism with the permanent magnet wheel is proposed to realize the function of the stability to walk on the outer wall and good ability to climb over the obstacle, in order to replace manual inspection of pipelines in a safer and more efficient way when it is equipped with the testing equipment. To determine the driving force required, the minimum magnetic force meeting the force balance condition of stable adsorption of the robot needs to be calculated first; the size of the permanent magnet wheel is designed and determined based on the magnetic force analysis model of the permanent magnet wheel established by Maxwell. Kinematics simulation of the robot based on Adams software is carried out and the ability to climb over the obstacle is verified.

Objective To construct a risk factor assessment scale for silent aspiration in comatose patients with tracheotomy. Methods Based on literature review and group discussion, 29 experts were consulted in 2 rounds using Delphi method to optimize the items during September 2021 and May 2023. After the clinical data of 315 coma patients with tracheotomy admitted to our hospital between May 2014 and January 2018 were retrospectively collected, 4 machine learning models, including Logistic Regression (LR), eXtreme Gradient Boosting (XGBoost), Naive Bayes (NB) and Support Vector Machine (SVM), were established. Receiver operating characteristic (ROC) curve was drawn and area under the ROC curve (AUC), sensitivity, specificity, positive predictive value, negative predictive value, F1 score and accuracy were calculated to evaluate the effectiveness. Results Finally, a total of 21 risk assessment indicators involving 50 grade items were identified. The positive coefficients of the 2 rounds of expert consultation were 96.7% and 100%, respectively. The authority coefficients for the 2 rounds were 0.88, and the Kendall coordination coefficients were 0.362 and 0.222 (P < 0.001), respectively. The coefficients of variation of the importance and accuracy of each item ranged from 0.080 to 0.299 and from 0.091 to 0.191, respectively. The AUCs of LR, NB, XGboost and SVM models were 0.977, 0.981, 0.953 and 0.978, respectively. Conclusion Our study identifies 21 risk assessment indicators, including endotracheal tube type, tracheotomy catheter balloon pressure, mechanical ventilation, nasal feeding, gastric remnant, swallowing function, cough reflex and oral cleanliness, and 50 grade items. Clinical verification shows that the constructed risk assessment indicators have good predictive efficacy and can provide reference for the assessment of silent aspiration risk in coma patients with tracheotomy.

The objective was to examine the pooled effects of antibiotic–probiotic combinations by examining the cure rate and recurrence rate for bacterial vaginosis (BV). A systematic literature search was conducted from electronic databases. All parallel randomized controlled trials (RCTs) that focused on the effects of antibiotics combined with intravaginal probiotics were included. Cure rate and recurrence rate were the primary and secondary outcomes to be analyzed. Meta-analysis was conducted following the Cochrane handbook for Systematic Reviews of Interventions. As a result, of 923 studies identified, 11 articles involving 1,493 BV patients met the inclusion criteria and nine were available for meta-analysis. A meta-analysis of two studies evaluated the recurrence rate 12–16 weeks after treatment. Results showed a statistically significant difference favoring the antibiotics plus probiotics group vs the antibiotics plus placebo group (relative risk 0.62, 95% confidence interval [CI]: 0.45–0.85). The narrative review in one study indicated that the cure rate was higher in the antibiotics plus probiotics group, giving a significant HR ratio of 0.73 (95% CI 0.54–0.98) (p = 0.042). In conclusion, vaginal application of Lactobacillus in combination with antibiotics for the treatment of BV could be a promising method for both reducing the recurrence rate and relieving symptoms of BV.

Owing to the development issues of the Guangdong-Hong Kong-Macao Greater Bay Area in the new domestic and international situation, the content, challenges, and paths of innovation and development of the Greater Bay Area are explored from multiple dimensions, including economic, social, cultural, and institutional. The innovation and development of the Greater Bay Area should strengthen technological and industrial innovation capabilities, improve regional resilience to cope with external shocks, increase the mobility of intraregional factors, improve the well-being of the people's livelihood, enhance the capacity of spatial governance, promote integrated urban-rural development, and optimize the regional pattern of ecological security. The conclusion is that considering the innovation and development of the Greater Bay Area from a systemic and interconnected perspective is crucial for seeking innovations in various development fields and promoting coupling and coordination among them. Therefore, the region may acquire the agency that can continuously break through bottlenecks, resolve external shocks, and unlock new paths of development. We call for the strengthening of cross-field and cross-disciplinary collaborative research to contribute the power of geography to the realization of the development goals of the Guangdong-Hong Kong-Macao Greater Bay Area.

With the rapid development of modern information technologies, their integration into all areas of education is accelerating, which contributes to the penetration of innovations into the education space. The author emphasizes that the design of many educational technologies was focused on the goals of education and included a sufficient number of educational concepts and elements. However, if teachers blindly adhere to the traditional concept of “technology is only a tool”, then this creates a sense of superiority of their own status and a narrow understanding of the value of technology. The author relies in his research on the latest achievements in the field of not only high technologies that are used in education, but also on psychological and social research on the impact of the latter both on education and on a person. The author proposes to perceive technologies in the context of a new culture, and shows possible ways of their more adequate use. Working with artificial technological objects is not only the acceptance of an artificial object, but also the adoption of a technical culture, which indicates a new cultural relationship between people and technology, and vice versa. On the basis of analyzing the phenomenon and essence of contemporary information technology, the author of this article tries to find out the problems existing in the application of contemporary information technology in education through a questionnaire survey, and reflects on the influence of technology on teachers and students in the education system. The answers of the survey participants made it possible to present a picture of the use of information technologies in education as a holistic and complex process. The analysis of the results obtained, as well as everyday practical training in the skills of using high technologies, enabled the author to establish that the influence of information technologies on education is complex, this is a new stage in the development of education as a whole, which allows us to characterize the process of their use as a holistic system. The influence of technology has completely changed all structures and all participants in education. The results of the survey also made it possible to identify a number of problems that indicate shortcomings in the modern space of education, the didactic nature of learning in the sense of conveying and receiving information in new conditions (we are talking not only about digitalization as a process, but also about changes aimed at transforming teaching methodology).

This study explored the predictive value of the monocyte-to-lymphocyte ratio (MLR) and platelet–lymphocyte ratio (PLR) in patients with acute-on-chronic liver failure (ACLF). A retrospective analysis was carried out on 40 patients with ACLF from January 2018 and August 2019 in our hospital. The patient’s clinical information during hospitalization was collected, and their survivals were followed for 3 months. MLR and PLR values of patients were compared, and the correlation between liver function indicators and prognosis was analyzed. We observed that MLR levels in the survival and death groups were 0.521 (0.311, 0.827) and 0.741 (0.442, 1.121), respectively. MLR levels were markedly enhanced in the death group compared to the survival group (P = 0.021). The receiver operating characteristic curve (ROC) exhibited that the area under the ROC curve and 95% confidence interval for the survival group was 0.641 (0.528–0.757). Survival analysis demonstrated that the 3-month survival of the high MLR group was markedly lower than that of the low MLR group (P = 0.001). Multivariate regression exposed that MLR and PLR were independent prognostic factors for ACLF. MLR and PLR could be prospective prognosticative markers of ACLF.

ObjectiveDesert vegetation is an indispensable part of desert ecosystems, and its conservation and restoration are crucial. Accurate identification of desert plants is an indispensable task, and is the basis of desert ecological research and conservation. The complex growth environment caused by light, soil, shadow and other vegetation increases the recognition difficulty, and the generalization ability is poor and the recognition accuracy is not guaranteed. The rapid development of modern technology provides new opportunities for plant identification and classification. By using intelligent identification algorithms, field investigators can be effectively assisted in desert plant identification and classification, thus improve efficiency and accuracy, while reduce the associated human and material costs.MethodsIn this research, the following works were carried out for the recognition of desert plant: Firstly, a training dataset of deep learning model of desert plant images in the arid and semi-arid region of Xinjiang was constructed to provide data resources and basic support for the classification and recognition of desert plant images.The desert plant image data was collected in Changji and Tacheng region from the end of September 2021 and July to August 2022, and named DPlants50. The dataset contains 50 plant species in 13 families and 43 genera with a total of 12,507 images, and the number of images for each plant ranges from 183 to 339. Secondly, a migration integration learning-based algorithm for desert plant image recognition was proposed, which could effectively improve the recognition accuracy. Taking the EfficientNet B0-B4 network as the base network, the ImageNet dataset was pre-trained by migration learning, and then an integrated learning strategy was adopted combining Bagging and Stacking, which was divided into two layers. The first layer introduced K-fold cross-validation to divide the dataset and trained K sub-models by borrowing the Stacking method. Considering that the output features of each model were the same in this study, the second layer used Bagging to integrate the output features of the first layer model by voting method, and the difference was that the same sub-models and K sub-models were compared to select the better model, so as to build the integrated model, reduce the model bias and variance, and improve the recognition performance of the model. For 50 types of desert plants, 20% of the data was divided as the test set, and the remaining 5 fold cross validation was used to divide the dataset, then can use DPi(i=1,2,…,5) represents each training or validation set. Based on the pre trained EfficientNet B0-B4 network, training and validation were conducted on 5 data subsets. Finally, the model was integrated using soft voting, hard voting, and weighted voting methods, and tested on the test set.Results and DiscussionsThe results showed that the Top-1 accuracy of the single sub-model based on EfficientNet B0 network was 92.26%~93.35%, the accuracy of the Ensemble-Soft model with soft voting, the Ensemble-Hard model with hard voting and the Ensemble-Weight model integrated by weighted voting method were 93.63%, 93.55% and 93.67%, F1 Score and accuracy were comparable, the accuracy and F1 Score of Ensemble-Weight model integrated by weighted voting method were not significantly improved compared with Ensemble-Soft model and Ensemble-hard model, but it showed that the effect of weighted voting method proposed in this study was better than both of them. The three integrated models demonstrate no noteworthy enhancements in accuracy and F1 Score when juxtaposed with the five sub-models. This observation results suggests that the homogeneity among the models constrains the effectiveness of the voting method strategy. Moreover, the recognition effects heavily hinges on the performance of the EfficientNet B0-DP5 model. Therefore, the inclusion of networks with more pronounced differences was considered as sub-models. A single sub-model based on EfficientNet B0-B4 network had the highest Top-1 accuracy of 96.65% and F1 Score of 96.71%, while Ensemble-Soft model, Ensemble-Hard model and Ensemble-Weight model got the accuracy of 99.07%, 98.91% and 99.23%, which further improved the accuracy compared to the single sub-model, and the F1 Score was basically the same as the accuracy rate, and the model performance was significant. The model integrated by the weighted voting method also improved accuracy and F1 Score for both soft and hard voting, with significant model performance and better recognition, again indicating that the weighted voting method was more effective than the other two. Validated on the publicly available dataset Oxford Flowers102, the three integrated models improved the accuracy and F1 Score of the three sub-models compared to the five sub-models by a maximum of 4.56% and 5.05%, and a minimum of 1.94% and 2.29%, which proved that the migration and integration learning strategy proposed in this paper could effectively improve the model performances.ConclusionsIn this study, a method to recognize desert plant images in natural context by integrating migration learning and integration learning was proposed, which could improve the recognition accuracy of desert plants up to 99.23% and provide a solution to the problems of low accuracy, model robustness and weak generalization of plant images in real field environment. After transferring to the server through the cloud, it can realize the accurate recognition of desert plants and serve the scenes of field investigation, teaching science and scientific experiment.

It is a hot topic to investigate resource allocation in fog computing. However, currently resource allocation in fog computing mostly supports only fixed resources, that is, the resource requirements of users are satisfied with a fixed amount of resources during the usage time, which may result in low utility of resource providers and even cause a waste of resources. Therefore, we establish an integer programming model for the time-varying multidimensional resource allocation problem in fog computing to maximize the utility of the fog resource pool. We also design a heuristic algorithm to approximate the solution of the model. We apply a dominant-resource-based strategy for resource allocation to improve resource utilization as well as critical value theory for resource pricing to enhance the utility of the fog resource pool. We also prove that the algorithm satisfies truthful and individual rationality. Finally, we give some numerical examples to demonstrate the performance of the algorithm. Compared with existing studies, our approach can improve resource utilization and maximize the utility of the fog resource pool.

This paper discusses the critical role of art therapy in solving various psychological problems, and introduces an innovative immersive and interactive art therapy mechanism based on artificial intelligence (AI), which combines machine learning and AI algorithms to realize embodied interactions between the learner, the machine, and the environment.The study analyzes the changes of students’ status before and after receiving art therapy in terms of various dimensions, including students’ social avoidance, general well-being, and self-emotions. Using regression modeling, the study validated the positive effects of art therapy on students’ mental health, cognitive abilities, and depression levels. It showed that art therapy had a statistically significant impact on improving students’ mental health, cognition, and reducing depressive symptoms at the 1% level of significance. Students who participated in art therapy had a 0.329 unit increase in mental health scores compared to non-participants, and this study provides a valuable reference and idea for the application of expressive art therapy in mental health education.

Planetary gear train is mainly used for power transmission, so it is of great significance to study its self-locking and efficiency. In this study, the self-locking analysis and efficiency maximization design of a 3K-H planetary gear train are carried out. Firstly, the efficiency of the positive and negative mechanism of the gear train is calculated using the transmission ratio method. Then, a unified formula for the efficiency of the planetary gear train is summarized. Furthermore, the efficiency curve is drawn by Matlab. Next, the trend of efficiency change of the planetary gear train and the conditions for realizing self-locking are analyzed. Finally, how to maximize the efficiency of the opposite mechanism under the condition of self-locking is studied.

Objective To explore and construct an optimization strategy for large-scale nucleic acid collection mode in the emergency conditions of putting the makeshift COVID-19 hospitals into use. Methods A self-pre- and post- control study was conducted on 542 COVID-19 patients in the makeshift hospital located in National Exhibition and Convention Center (Shanghai) in April 2022. According to the elution period with an interval of 1 week, nucleic acid collection was carried out in red-zone package mode, in-cabin and out-cabin linkage mode and integrated precision sampling mode, and the consuming time of work was recorded. The electronic survey used to detect the satisfaction of patients. At the same time, the results of the levels of teamwork, patient cooperation and satisfaction of 106 medical staff participating in nucleic acid testing under the above different sampling modes were collected. Results The work consumption time of the integrated precision sampling mode was significantly shorter than that of the other two sampling modes (P < 0.01), the percentage patient satisfaction rate in the integrated precision sampling mode was higher than that of the other two sampling modes (P < 0.05), and the team cooperation, patient cooperation, and the percentage of satisfaction of medical staff were significantly higher than those of the other two sampling modes (P < 0.01) in the integrated precision sampling mode. Conclusion The integrated precision sampling mode can significantly shorten the sampling time in large-scale nucleic acid collection, effectively improve the degree of cooperation between doctors and patients in sampling work and increase the satisfaction of patients and medical staff during the sampling process.

Multi Core Fiber (MCF) is an important transmission medium of Space Division Multiplexing (SDM) technology, which can significantly enhance the communication capacity of existing optical fiber. However, MCF has the problems of high structural complexity, difficult to test, and no test standard for parameters. According to the structural characteristics, combined with the technical experience in the development, this paper standardize the splicing method and the parameters testing method of MCF, which lays the foundation for the large-scale commercialization of MCF in the future.

C30H36F2N6O9S, orthorhombic, P212121 (no. 19), a = 5.2364(8) Å, b = 10.0250(14) Å, c = 59.689(9) Å, V = 3133.4(8) Å3, Z = 4, Rgt(F) = 0.0384, wRref(F2) = 0.0969, T = 170 K.

【Background and objective】 Hebei province is the second largest agricultural province in terms of agricultural counties. Improving county-level agricultural economy is hence important for developing the provincial economy. This, however, is held back by scarcity and uneven distribution of its water resources. Effective irrigation has been proposed as a solution to this dilemma, but it is unknown if this could slow down the economic growth as suspected over the past few years. The objective of this paper is to elucidate the impact of effective irrigation on agricultural economy at country level. 【Method】 The analysis is based on data collected from 2015 to 2017 from 170 districts and counties across the province. The Moran’s I index and the Getis-Ord Gi* indexes are used to calculate the spatial correlation and clarify the spatiotemporal evolution of the agricultural economy in these counties/districts. Spatial autoregressive and panel threshold regression models are used to analyze the effect of effective irrigation on agricultural economy. 【Result】 Agricultural economy is uneven between these counties, but its spatial distribution pattern remains stable, all showing a continuous improvement. SDM model shows that the counties/districts which had implemented effective irrigation not only inhibited their own agricultural economy but also their adjacent neighbour. Panel threshold regression model shows that with the two thresholds taken as the demarcation point, the effective irrigation had a three-stage impact on agricultural economic growth: noticeably inhibited, continuously inhibited, and noticeably increased. There are 166 districts/counties which are in the middle transfer range, at which an increase in effective irrigation had a continuous inhibitory effect on their agricultural economy. The deficiencies of natural resources make it difficult to develop and utilize water resources, and natural disasters often affect irrigation benefits. The investment in irrigation facilities is large and most counties are still in recovering the construction costs. These are the main reasons behind the slowed agricultural economic growth in most of these counties. While constructing water conservancy engineering facilities is essential to improving water resource utilization, other methods such as developing water-saving irrigation technologies, improving management and agricultural policies is also helpful to improve quality and efficiency of agricultural production. 【Conclusion】 The analysis shows that implementation of effective irrigations by some counties in Hebei province has a negative impact on their agricultural economy, and the underlying reasons vary.

Objective To investigate the changes of brain activation and brain network connectivity in patients with spinal cord injury (SCI). Methods A total of 20 patients with SCI were selected from Qilu Hospital of Shandong University from January to October 2021, including 8 patients with simple lower extremity involvement (paraplegia group) and 12 patients with all limbs involvement (tetraplegia group), and 10 healthy controls with matched baseline data with the SCI group were included in the same period. Functional near⁃infrared spectroscopy (fNIRS) was used to collect the data of cerebral oxyhemoglobin (HbO2) in the bilateral prefrontal lobe (LPFC/RPFC), motor cortex (LMC/RMC) and occipital lobe (LOL/ROL). The resting HbO2 β values was calculated by generalized linear model to evaluate the activation degree of the cerebral cortex covered by different detection channels, the correlation between HbO2 β values was calculated by Pearson correlation analysis and partial correlation to analysis different detection channels [partial correlation coefficient (r) was defined as functional connectivity strength] to evaluate the functional connectivity of the brain network. Results 1) Degree of brain activation: compared with the control group, the HbO2 β values corresponding to channel 2 (t=⁃2.482, P=0.020), channel 8 (t=⁃3.315, P=0.003) and channel 16 (t=⁃2.738, P=0.011) was increased in the tetraplegia group, while the HbO2 β value corresponding to channel 25 was decreased (t=2.104, P=0.045), and the HbO2 β value of channel 8 was increased (t=⁃2.475, P=0.020) in paraplegia group. Compared with the tetraplegia group, the HbO2 β values in channel 17 (t=2.552, P=0.017) and channel 25 (t=2.342, P=0.027) were increased in the paraplegia group. The value of HbO2 β in the left prefrontal lobe of tetraplegia group was significantly higher than that of control group (t=2.652, P=0.013). 2) The number of functional connections between different channels and cerebral cortex: the proportion of channels related to motor cortex in different groups was 94.12% in the paraplegia group (32/34), 82.76% in the tetraplegia group (24/29), and only 74.36% in the control group (29/39). 3) Functional connectivity strength in the brain: compared with the control group, the functional connectivity strength in the right motor area was weakened in both the paraplegia group (t=4.572, P=0.000) and the tetraplegia group (t=4.822, P=0.000). Conclusions There are abnormalities in resting brain activation and functional connectivity of brain network after SCI, which are manifested as local enhancement of spontaneous neural activity in some brain regions and abnormal functional connectivity in cerebral cortices and brain regions.

Objective: The effect of ultrasonic-assisted ionic crosslinking method on the peppermint capsule roundness was studied. Methods: The optimal treatment process was obtained through response surface optimization method, and the quality indicators of peppermint capsule was analyzed. Results: The results showed that, the optimum conditions of ionic crosslinking method were calcium ion mass fraction of 0.4%, soaking time of 20 min, solid/liquid ratio of 1.3∶1.0 （mL/g）. Under the conditions, the strength of wet-capsule was 11.5 N, and the roundness of capsule was 0.033 mm. The optimum conditions of ultrasonic-assisted ionic crosslinking method were: ultrasonic time of 10 min, ultrasonic power of 105 W, ultrasonic temperature of 25 ℃. Under the conditions, the strength of wet-capsule was 14.7 N, and the roundness of capsule was 0.028 mm. Conclusion: Compared with the traditional ionic crosslinking method, the strength of the wet-capsule was increased by 27.8%, the roundness of the capsule product was decreased from 0.075 mm to 0.028 mm, and the product yield was increased from 83.7% to 98.3%, which showed that the quality of the peppermint capsule was obviously improved. The ultrasonic-assisted ionic crosslinking has the advantages of simple process and high efficiency, which could provide a reference for the development of capsule preparation technology.

Objective To summarize the clinical, imaging and genetic characteristics of spinocerebellar ataxia 2 (SCA2) families presenting as Parkinsonism. Methods and Results Two families with autosomal dominant SCA2 with Parkinson's syndrome diagnosed by genetic test in Peking University First Hospital from May 2019 to December 2020 were included. The probands in 2 families manifested as lead⁃pipe like rigidity and cerebellum ataxia. Electronystagmography (ENG) in proband of family 1 showed gaze nystagmus, understable saccade, decreased smooth tracking ability and disappeared optokinetic nystagmus, proband of family 2 showed slow saccade, decreased smooth tracking ability and decreased optokinetic nystagmus. Head MRI in both probands of 2 families showed slightly enlarged third ventricle, while the proband of family 2 showed atrophy in brain stem and cerebellar. Whole exome sequencing (WES) in 2 probands showed no gene mutations, Sanger sequencing showed dynamic mutation of ATXN2 gene and the copy number of cytosine⁃adenine⁃guanine (CAG) with 37 repeats. Two probands were finally diagnosed as SCA2, and two pedigrees were diagnosed as SCA2 pedigrees. Conclusions SCA2 can present as Parkinsonism, which is easily to be misdiagnosed as Parkinson's disease due to the effective treatment of levodopa. ENG is helpful in detecting subclinical cerebellar lesions. For Parkinsonism patients with family history, especially when cerebellar lesions are involved, ATXN2 gene testing is recommended.

Susceptibility ⁃weighted imaging (SWI) is a type of MRI developed based on gradient echo sequence (GRE). It is extremely susceptible to paramagnetic substances. The application of SWI has spread to various aspects of clinical practice, including the assessment of brain perfusion and collateral circulation, and the prognosis of intracranial venous system thrombosis. Furthermore, the sign of intracranial arterial thrombi on SWI helps to evaluate the etiology and outcome of ischemic stroke. To provide more information on the diagnosis, evaluation, and treatment of cerebrovascular diseases, we reviewed the application of SWI in cerebrovascular disease.

Aiming at the anchoring failure of heterogeneous rock strata, based on bolt bilinear strengthening constitutive model and considering the deterioration of tension and compression stiffness of bonded layer, a three-dimensional refined numerical calculation model of heterogeneous rock strata, bonded layer and bolt anchoring system was constructed. The stress transfer law of anchor bolt and deformation and failure characteristics of anchor system under granite-granite(H-H), granite-sandstone(H-S), sandstone-granite(S-H) and sandstone-sandstone(S-S) rock combinations were analyzed, and the influence law of different lithologic combinations on shear mechanical properties of anchor composite rock strata was revealed. The results show that the shear resistance is mainly in the local area of the bedding surface under compression shear state, and the maximum shear stress exists near the bedding surface. The peak value of bolt normal stress is related to the sequence of bolt penetration. Under the same boundary condition, the effect of rock bolt limiting shear movement of homogeneous hard rock is the best. The anchorage system near the bedding surface is prone to de-bonding failure and the position with large reduction rate of the stiffness of the bonded layer is always located in the soft rock part.

Plant income insurance has become an important part of agricultural insurance in China. It has been recommended to pilot since 2016 by Chinese government in several counties, and is now (2022) required to be implemented in all major grain producing counties in the 13 major grain producing provinces. The measurement of yield for plant income insurance in such huge volume urgently needs the support of remote sensing technology. Therefore, the development history and application status of remote sensing technology in the whole agricultural insurance industry was reviewed to help understanding the whole context circumstances of plant income insurance firstly. Then, the application scenarios of remote sensing technology were analyzed, and the key remote sensing technologies involved were introduced. The technologies involved include crop field plot extraction, crop classification, crop disaster estimation, and crop yield estimation. Research progress of these technologies were reviewed and summarized ,and the satellite data sources that most commonly used in plant income insurance were summarized as well. It was found that to obtain a better support for a development of plant income insurance as well as all crop insurance from remote sensing communities, issues existed not only in the involved remote sensing technologies, but also in the remote sensing industry as well as the insurance industry. The most two important technical problems in the current application scenario of planting income insurance are that: the plot extraction and crop classification are not automated enough; the yield estimation mechanism is not strong, and the accuracy is not high. At the industry level, the first issue is the limitation of the remote sensing technology itself in that the remote sensing is not almighty, suffering from limited data source, either from satellite or from other platform, laborious data preprocessing, and pricey data fees for most of the data, and the second is the compatibility between the current business of the insurance industry and the combination of remote sensing. In this regard, this paper proposed in total five specific suggestions, which are: 1st, to establish a data distribution platform to solve the problems of difficult data acquisition and processing and standardization of initial data; 2nd, to improve the sample database to promote the automation of plot extraction and crop classification; 3rd, to achieve faster, more accurate and more scientific yields through multidisciplinary research; 4th, to standardize remote sensing technology application in agricultural insurance, and 5th, to write remote sensing applications in crop insurance contract. With these improvements, the application mode of plant income insurance and probably the whole agriculture insurance would run in a way with easily available data, more automated and intelligent technology, standards to follow, and contract endorsements.

In the wind tunnel experiment, the existing CPU-based optical flow method takes too long to solve the velocity field of the fluorescent oil film, while the GPU-based optical flow method has the problem of insufficient utilization of GPU resources.To this end, a real-time measurement method of GPU fluorescent oil film motion path based on fluorescent oil film image segmentation and critical constraints is proposed.The fluorescent oil film time-series image is divided into blocks and processed in parallel according to the resources of the GPU, and the corresponding optical flow parallel computing strategy is created, that is, the advantages of the parallel pipeline architecture of the GPU and the shared memory are fully utilized to realize the optical flow calculation of each parallel block.At the same time, combined with the critical constraints between blocks, the number of iterative calculations is controlled by the iterative difference of the speed matrix of each block as a symbol.The experimental results show that the method proposed in this paper is 2 789.5 times faster than the traditional CPU-based optical flow method under the condition of ensuring the calculation accuracy of the velocity field of the fluorescent oil film motion, and the average speed of the GPU optical flow method of the whole frame image is improved.10.09 times and the real-time solution speed can reach 90 frames per second.

[Introduction] In order to determine soil strength parameters more accurately and reliably, based on domestic and foreign engineering experience and research results, this paper proposes a practical method to obtain the undrained shear strength of clay and the friction angle of sand based on static cone pentration test (CPT) and standard penetration test (SPT) data. [Method] Firstly, it introduced the method of rapid stratification based on the four basic data of CPT, aiming to divide the sand layer and clay laye. Then the method of calculating the empirical coefficient Nkt of the undrained shear strength of clay based on the CPT parameters was introduced. Finally, a method of comprehensively considering CPT and standard penetration data and calculating the internal friction angle of sand based on empirical methods was introduced. [Rseult] According to the method of CPT parameter estimation, the obtained clay undrained shear strength is well compared with the laboratory test results which can obtain the clay undrained shear strength profile. The combined method of CPT and SPT can measure the friction angle of sand reliably, which fills the gaps of test data due to the difficulty in obtaining sand samples from offshore exploration. [Conclusion] The method discussed in this paper can provide more reliable reference for determining th design values of soil strength considering the existing condition in which offshore survey methods are limited and the equipment resources are relatively scarce.

We study the boundedness of the oscillatory integral Tα,βf(x,y)=∫Q2f(x−γ1(t),y−γ2(s))e−2πit−β1s−β2t−α1−1s−α2−1dtds{T}_{\alpha ,\beta }f\left(x,y)=\mathop{\int }\limits_{{Q}^{2}}f\left(x-{\gamma }_{1}\left(t),y-{\gamma }_{2}\left(s)){e}^{-2\pi i{t}^{-{\beta }_{1}}{s}^{-{\beta }_{2}}}{t}^{{-\alpha }_{1}-1}{s}^{-{\alpha }_{2}-1}{\rm{d}}t{\rm{d}}s on Wiener amalgam spaces, where Q2=[0,1]×[0,1]{Q}^{2}=\left[0,1]\times \left[0,1] is the unit square in two dimensions, (x,y)∈Rn×Rm,γ1(t)=(tp1,tp2,…,tpn),γ2(s)=(sq1,sq2,…,sqm)\left(x,y)\in {{\mathbb{R}}}^{n}\times {{\mathbb{R}}}^{m},{\gamma }_{1}\left(t)=\left({t}^{{p}_{1}},{t}^{{p}_{2}},\ldots ,{t}^{{p}_{n}}),{\gamma }_{2}\left(s)=\left({s}^{{q}_{1}},{s}^{{q}_{2}},\ldots ,{s}^{{q}_{m}}) are homogeneous curves on Rn{{\mathbb{R}}}^{n} and Rm{{\mathbb{R}}}^{m}.

The high-temperature compressive properties are indispensable mechanical performance parameters for the structural design of composites, but it is difficult to be measured effectively by traditional techniques. In this study, the high temperature compressive experiment of carbon fiber reinforced plastics (CFRP) laminates was conducted in high-temperature experimental system based on digital image correlation (DIC) method. And the compressive properties, stress-strain curves and the evolution of axial full-field strain of CCF300/5228A with 0° and 90° ply-ups at 130℃ were obtained. Moreover, they were compared with those obtained at room temperature. Furthermore, the fracture analysis of the compressed specimens was carried out through scanning electron microscopy (SEM), meanwhile the effects of high temperature and lay-up on the compressive properties were discussed combining with the experimental results. Finally, an experimental verification was carried out and the results obtained demonstrated the feasibility and reliability of the experimental system and relevant experimental methods. The results show that the retention rate of 0° and 90° compressive strength at 130℃ are 70.5% and 62.6%, respectively, while the retention rate of compressive modulus are 88.0% and 75.4%, respectively, indicating that the strength and modulus of the laminates which are controlled by the matrix are more sensitive to high temperature.

Objective To report 3 cases of infratentorial superficial siderosis of central nervous system and analyze its etiology and clinical manifestations. Methods and Results The main clinical symptoms were recurrent headache or epilepsy (3 cases) with obvious hearing loss (2 cases); the appearance of cerebrospinal fluid of lumbar puncture was cloudy and bloody fluid, with increased red blood cell count and protein quantity (2 cases). MRI scan of head or cervical spine showed siderosis deposition on the surface of cerebellum hemisphere, pons and midbrain without enhancement, and occupying lesion at jugular foramen was seen at the same time (Case 1); tortuous vessels on the surface of cervical spinal cord, epidural effusion at the level of C6⁃7 vertebral body, C7 dural defect (Case 2) or paraventricular hemorrhage (Case 3). There were no abnormal findings in angiography of the whole brain. The clinical diagnosis was infratentorial superficial siderosis of central nervous system (type Ⅰ 2 cases, type Ⅱ 1 case). The causes were neurilemmoma, traumatic dural defect or cerebrovascular malformation. According to the cause of the disease, the left C7 dural defect repair (Case 2) or left occipital lobe hematoma removal (Case 3) were performed. The patients' condition improved significantly and the headache disappeared. Conclusions The etiology of infratentorial superficial siderosis of central nervous system is heterogeneous. Detailed auxiliary examination is of great significance in avoiding misdiagnosis or missed diagnosis.

Insect problem has been one of the most severe problems in agriculture and forestry, which causes great economic losses to the primary industry in China. For a long time, the use of chemical insecticides for insect control has led to many issues, such as pollution, insect resistance, etc. Therefore, in recent years, the research and application on biological pesticides of broad spectrum, high efficiency and low toxicity is increasing. Insecticidal proteins, especially those of microbial source, as an important branch of biological insecticides, have been continuously developed and applied due to their excellent insecticidal potential. This paper aims to classify the information on insecticidal proteins from microorganism over the world, and to provide fresh opinions for the application of insecticidal proteins in agriculture, forestry and other industries in China.